Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoid malignancy in adults. Although 40 percent of DLBCL patients can be cured with combination chemotherapy, the majority will ultimately die of their disease. Prognostic models based on pretreatment clinical characteristics identify DLBCL patients with different likelihoods of being cured with current therapy. However, these clinical models do not address the intrinsic molecular and cellular heterogeneity in this disease. The heterogeneity in clinical outcomes, molecular genetics and putative cells of origin in DLBCL suggests that there are biologically discrete subsets of the disease that remain to be defined. In this proposal, we will utilize RNA expression profiling on microarrays and pattern recognition algorithms to define the signatures of cured and fatal DLBCLs and improve our prognostic models and treatment strategies. Initial tumor expression profiles from 58 newly-diagnosed DLBCL patients have been used to develop a model which identifies 2 categories of patients with dramatically different 5-year survivals (72 percent vs. 9 percent, p = .0003). Preliminary analyses of the risk-related genes and their associated nearest neighbors identify several discrete features associated with outcome including potential differences in responses to B-cell receptor signaling and associated serine/threonine phosphorylation pathways and downstream regulators of apoptosis. We will build on these preliminary analyses to develop molecular signatures of outcome (Specific Aim 1), elucidate specific genetic, developmental and signaling pathways that contribute to these outcome signatures (Specific Aim 2), and utilize the resulting information to develop rational risk-related approaches to therapy (Specific Aim 3).